SRL is a shallow semantic analysis technique that is useful for many applications, such as information extraction, machine translation, etc. Given a sentence, SRL aims to find out the predicates and their arguments in the sentence and assign a semantic role label for each argument. For example, the sentence “Foreign invested companies have become the growing point of investment in China's foreign trade.” will be labeled as “[Foreign invested companies]A1 have [become]Pred [the growing point of investment in China's foreign trade]A2.” in SRL. In the example above, “become”, labeled as “Pred”, is a predicate. A predicate usually stands for an action and has several related arguments. “Foreign invested companies”, labeled as “A1”, is the actor. “the growing point of investment in China's foreign trade”, labeled as “A2”, is the new state that the actor becomes.
A widely used standard for SRL is the PropBank annotation standard, which defines a role set containing six key argument types: A0, A1, A2, A3, A4, A5, and many adjunct argument types whose label begins with “AM”, such as AM-TMP, AM-ADV, etc. A detailed description of the PropBank annotation standard can be found in Martha Palmer, Daniel Gildea, and Paul Kingsbury. 2005. The Proposition Bank: An Annotated Corpus of Semantic Roles. Computational Linguistics, 31(1): 71-106.
The example above shows that by analyzing the predicate-argument structure of a sentence, SRL can extract the semantic framework of the sentence, which makes SRL very useful for many applications such as Information Extraction, Machine Translation, Automatic Summarization, etc.
In applications such as Machine Translation, SRL is needed to be performed on bilingual sentence translation pairs. Table 1 shows an example of a Chinese-English sentence translation pair.
TABLE 1   In recent years the pace of opening up to the outside of China's constructionmarket has further accelerated
Performing bilingual SRL on the sentence pair above, we should get the following results:

Different from a monolingual SRL task, in a bilingual SRL task, a pair of sentences are presented at the same time. Conventional methods for bilingual SRL performs monolingual SRL on each side of bitext separately. However, the accuracy of the conventional method is quite low and the SRL results are often inconsistent between two sides of bitext.